How Financial Organisations Can Maximise the Strategic Value of Quality Assurance Data

Derek Corcoran, CEO of Scorebuddy, the world’s leading quality management platform for contact centers

 

Data is the driving force behind contemporary business and in financial institutions, that’s doubly true. It doesn’t just help you gain a clear view of your company’s key performance indicators (KPIs), but supports customer experience, risk mitigation, compliance, team productivity, and operational efficiency. The more data you have access to, the more successful your business has the potential to be. Quality Assurance (QA) can be a mine of information allowing you to not just gain a better understanding of your business, but to take real strategic control.

Unlocking the potential of QA data in finance

QA and business intelligence (BI) have become almost inextricably linked. While QA measures, evaluates, and reviews a business’ services, products, and systems, ensuring that standards are always met, the data provided should afford the insights necessary to shape the strategies and technological requirements of the organisation, directly feeding into BI.

If used well, QA data can be applied to augment and develop a wide range of business procedures and KPIs. From customer experience (CX), satisfaction, and retention, where QA insights can help to identify pain points within the customer journey and improve CSAT, to regulatory compliance and cost reduction, where QA system tools, such as call recording and scorecards, can help businesses to monitor and address compliance issues and avoid fines, as well as reducing overheads through enhanced operational efficiencies, reduction of employee churn, and risk mitigation.

Although QA holds the potential to massively influence BI and wider company strategy, few financial businesses manage to use QA data to their best advantage. And that’s primarily because the data comes from such varying sources and unless specific systems have been set in place to allow the easy access and consolidation of that data, much of it goes to waste. So, how can businesses remove that barrier?

Finding ways to improve the application of QA data in financial organisations

Derek Corcoran

The greatest challenge in making use of QA data is the fact that it comes from multiple channels. In finance, QA can mean everything from data security and cloud accessibility to third-party integration, and customer service touch points. These are typically managed by multiple departments, each with their own systems, procedures, and structures. Some companies even deploy unique technology products for different departments, meaning that it can be really difficult to amalgamate data from different sources. Whether for report creation, decision-making, or strategy planning.

This not only makes life more difficult for all concerned with those processes, but it takes considerably longer to get anything done. This is ridiculous at a time when technology has advanced to a place of genuine artificial intelligence (AI), and machine learning (ML) is being used for most other time-consuming previously manual processes. It’s surely time for technology to assist with QA data management too.

With the right tools, businesses can access and manage multiple metrics and datasets a lot more easily and efficiently. Tech can be used to open data streams from a variety of sources, altering the format to allow for greater accessibility, while deploying simple drag and drop data gathering tools to enable cohesive report creation from multi-source investigations, streamlining decision-making and building efficiency into the core of every business.

Where should QA data come from?

QA data sources will vary according to business type. Even different financial institutions will be interested in different metrics. But as a general rule, it’s a good idea to look at more than just numerical data. While most businesses will focus on sales numbers, complaints raised, compliance concerns, and customer service times, you need to remember that there are other data sources available. So, think about quality as well as quantity. Review customer (and sales agent) feedback to build context into your numbers, because while the numbers can clearly indicate that customer retention is falling, they will rarely show you the reason for that shift.

Quality Assurance holds enormous power for businesses. It can provide the insights needed to successfully manage change and strategically plan for maximum productivity, efficiency, and revenue. Its potential is almost limitless. But to unleash that potential, financial organisations have to learn how to effectively manage that data. Technology could provide the answer.

 

 

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